Signal Quality Index Estimator for Complex-Lead type ECG beat detectors

Abstract: The Electro Cardio Gram is a very valuable clinical tool to access the electric function of the heart. It provides insight into the different phases of the heart beat and various kinds of disorders which may affect them. In the past decades various algorithms to detect and delineate ECG beats have been developed. The complex-lead based algorithms compute a virtual-lead by averaging the samples of an arbitrary number of channels. In this study exponential weighted moving powers based estimates for the skewness, kurtosis and signal to noise ratio are used to select the channels which are included in the resulting complex lead signal. According to these parameters the channels are labelled bad, poor, scaled and good. A weighted average is used to to compute the next sample of the complex lead from the channels labelled good and scaled. The 75 30minutes records of the ”St.-Petersburg Institute of Cardiological Technics 12-lead Arrhythmia Database” are used to evaluate the proposed approach. The average sensitivity increases to 99.61% and to 99.63% in total compared to 99.57% and 99.59% for the standard approach. The average and overall specificity increases to 99.65% and the F1 and F-M scores to 0.9964. This shows that the estimates provide sufficient information about the quality, to successfully reduce the distortion of the complex-lead signal by artefacts and strong muscle signals while avoiding the additional time delay imposed by standard window based methods.

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: Signal Quality Index Estimator for Complex-Lead type ECG beat detectors ; volume:10 ; number:3 ; year:2024 ; pages:1-4 ; extent:4 ; Current directions in biomedical engineering ; 10, Heft 3 (2024), 1-4 (gesamt 4)

Contributors, Places and Time

• Creator: Hintermüller, Christoph ; Blessberger, Hermann ; Steinwender, Clemens

Further information

• DOI: 10.1515/cdbme-2024-1101
• URN: urn:nbn:de:101:1-2410101548459.086916939635
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 15.08.2025, 7:30 AM CEST